Least squares projection twin support vector machine with universum

doi:10.3969/j.issn.1000-1565.2016.01.015

Abstract

Abstract: A new algorithm is constructed,called least squares projection twin support vector machine with Universum(ULSPTSVM).By adding Universum data,samples are introduced which have no relation with the samples of classification,which have a priori domain information.In addition,in order to further enhance the performance of ULSPTSVM,the method is extended to recursive learning method.Experiments show that ULSPTSVM can directly improve the training time of twin support vector machine with Universum(UTSVM),and in most cases the experimental accuracy is better than least squares projection twin support vector machine(LSPTSVM).

Key words: Universum data, support vector machine, twin support vector machine, projection

CLC Number:

TP391.4

LU Shuxia,TONG Le,ZHU Chenxu. Least squares projection twin support vector machine with universum[J]. Journal of Hebei University (Natural Science Edition), 2016, 36(1): 94-99.

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